optimizing agriclutural pridiction
Budget: ₹1,500 – ₹12,500 INR
The goal of this research is to use machine learning to help optimise land for
maximum crop yield by efficiently utilising land resources in food crop cultivation. Crop output
is heavily reliant on how well basic land requirements are met; land relates to soil type, soil
nutrients, water content, temperature, humidity, and water quality, among other things.
The ultimate goal is to maximise production by automatically reducing water
consumption, fertiliser use, and the amount of arable land. The goal of this work is to find the
best agricultural production plan by merging numerous criteria into a utility function while
keeping a set of restrictions in mind, such as land, labour, available capital, and so on. We used
multicriteria techniques to extend procedures for the analysis and modelling of agricultural
systems for this goal.
maximum crop yield by efficiently utilising land resources in food crop cultivation. Crop output
is heavily reliant on how well basic land requirements are met; land relates to soil type, soil
nutrients, water content, temperature, humidity, and water quality, among other things.
The ultimate goal is to maximise production by automatically reducing water
consumption, fertiliser use, and the amount of arable land. The goal of this work is to find the
best agricultural production plan by merging numerous criteria into a utility function while
keeping a set of restrictions in mind, such as land, labour, available capital, and so on. We used
multicriteria techniques to extend procedures for the analysis and modelling of agricultural
systems for this goal.